Detecting light in whispering-gallery-mode resonators

An optical device including a whispering gallery mode (WGM) optical resonator configured to support one or more whispering gallery modes; and a photodetector optically coupled to an exterior surface of the optical resonator to receive evanescent light from the optical resonator to detect light inside the optical resonator

Next-to-next-to-leading-order epsilon expansion for a Fermi gas at infinite scattering length

We extend previous work on applying the epsilon-expansion to universal properties of a cold, dilute Fermi gas in the unitary regime of infinite scattering length. We compute the ratio xi = mu/epsilon_F of chemical potential to ideal gas Fermi energy to next-to-next-to-leading order (NNLO) in epsilon=4-d, where d is the number of spatial dimensions. We also explore the nature of corrections from the order after NNLO.Comment: 28 pages, 14 figure

The effect of limited cognitive resources on communication disturbances in serious mental illness

Semantically incoherent speech is a pernicious clinical feature of serious mental illness (SMI). The precise mechanisms underlying this deficit remain unclear. Prior studies have found that arousal of negative emotion exaggerates the severity of these communication disturbances; this has been coined "affective reactivity". Recent research suggests that "cognitive reactivity" may also occur, namely reflecting reduced "on-line" cognitive resources in SMI. We tested the hypothesis that communication disturbances manifest as a function of limited cognitive resources in SMI above and beyond that associated with state affectivity. We also investigated individual differences in symptoms, cognitive ability, and trait affect that may be related to cognitive reactivity. We compared individuals with SMI (n=52) to nonpsychiatric controls (n=27) on a behavioral-based coding of communication disturbances during separate baseline and experimentally-manipulated high cognitive-load dual tasks. Controlling for state affective reactivity, a significant interaction was observed such that communication disturbances decreased in the SMI group under high cognitive-load. Furthermore, a reduction in communication disturbances was related to lower trait and state positive affectivity in the SMI group. Contrary to our expectations, limited cognitive resources temporarily relieved language dysfunction. Implications, particularly with respect to interventions, are discussed

Inferring Properties of Graph Neural Networks

We propose GNNInfer, the first automatic property inference technique for GNNs. To tackle the challenge of varying input structures in GNNs, GNNInfer first identifies a set of representative influential structures that contribute significantly towards the prediction of a GNN. Using these structures, GNNInfer converts each pair of an influential structure and the GNN to their equivalent FNN and then leverages existing property inference techniques to effectively capture properties of the GNN that are specific to the influential structures. GNNINfer then generalizes the captured properties to any input graphs that contain the influential structures. Finally, GNNInfer improves the correctness of the inferred properties by building a model (either a decision tree or linear regression) that estimates the deviation of GNN output from the inferred properties given full input graphs. The learned model helps GNNInfer extend the inferred properties with constraints to the input and output of the GNN, obtaining stronger properties that hold on full input graphs. Our experiments show that GNNInfer is effective in inferring likely properties of popular real-world GNNs, and more importantly, these inferred properties help effectively defend against GNNs' backdoor attacks. In particular, out of the 13 ground truth properties, GNNInfer re-discovered 8 correct properties and discovered likely correct properties that approximate the remaining 5 ground truth properties. Using properties inferred by GNNInfer to defend against the state-of-the-art backdoor attack technique on GNNs, namely UGBA, experiments show that GNNInfer's defense success rate is up to 30 times better than existing baselines.Comment: 20 pages main paper, 10 pages for appendi